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Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model
Published 2000“…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. Therefore, purchasing shares in this sector is very attractive for a long-term investment period, but may have a high risk of committing it as a result of fluctuations in the mean and variance of the estimate. …”
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A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), Hartigan- Wong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), HartiganWong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), HartiganWong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), Hartigan-Wong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi
Published 2017“…Details of the algorithms which include entropy estimation which would enhance the application of a proper risk measure like entropy, is provided. …”
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Slice sampler algorithm for generalized pareto distribution
Published 2018“…Finally, the slice sampler algorithm was employed to estimate the re- turn and risk values of investment in Malaysian gold market.…”
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Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network
Published 2011“…A new learning algorithm called the ensemble dual algorithm for estimating the mass-flow rate of the flow after leakage is proposed. …”
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Artificial Neural Network in Predicting Risk Exposure in Malaysian Shipyard Industry
Published 2024“…Risk exposure prediction is an important task in risk management and control. …”
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Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility
Published 2018“…The results of simulation reveal that the proposed estimators are efficient based on the bias, variance, and mean square error. …”
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Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
Published 2018“…Two classification methods, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used in order to investigate the performance of classification accuracy for this E-nose system. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article -
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All-in-1 adverse drug reaction reporting system / Long Chiau Ming … [et al.]
Published 2014“…Unfortunately, low ADR reporting numbers are known to inflate the risk estimates for many less commonly used drugs especially among paediatric, making them less reliable and sensitive for early detection. …”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation
Published 2016“…Meanwhile, a set of descriptors corresponding to Elliptic Fourier Features shape description is extracted for each defect and is evaluated for each cluster to use for clustering and classification part. The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. …”
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Discretized Markov Chain in Damage Assessment Using Rainflow Cycle with Effects of Mean Stress On An Automobile Crankshaft
Published 2016“…The fatigue mean stresses were used to estimate the effects of the mean stress on the fatigue strength of the component under service loading condition. …”
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The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach
“…A variation of k-NN algorithms were tested based on the number of neighbours, as well as the weight and the type of distance metric used. …”
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